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SozioTex-Sociotechnical systems in the Textile Industry: Interdisciplinary Competence Build-up in Human-machine Interaction Facing Demographic Change | OMICS International
ISSN: 2165-8064
Journal of Textile Science & Engineering
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SozioTex-Sociotechnical systems in the Textile Industry: Interdisciplinary Competence Build-up in Human-machine Interaction Facing Demographic Change

Gloy YS2*, Lemm J2, Hansen-Ampah A1, Saggiomo M2, Lohrer M2 and Kerpen D1

1Institute of Sociology (IfS) at RWTH Aachen University, Aachen, Germany

2Institut für Textiltechnik (ITA) at RWTH Aachen University, Aachen, Germany

*Corresponding Author:
Gloy YS
Institut für Textiltechnik der RWTH Aachen University
Otto-Blumenthal-Street 1, 52074, Aachen, Germany
Tel: +49-241-803470
Email: [email protected]

Received Date: October 16, 2015; Accepted Date: December 07, 2015; Published Date: December 14, 2015

Citation: Gloy YS, Kerpen D, Lemm J, Hansen-Ampah A, Saggiomo M, et al. (2015) SozioTex-Sociotechnical systems in the Textile Industry: Interdisciplinary Competence Build-up in Human-machine Interaction Facing Demographic Change. J Textile Sci Eng 5:226. doi: 10.4172/2165-8064.1000226

Copyright: © 2015 Gloy YS, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

High-wage countries are on the brink of change, due to social and technological effects. In this paper, we will first give an outlook on both these effects concerning the German textile industry. Second, we will shortly describe the interdisciplinary build-up of our research group which influences the way how we address our research issues. Finally, we will outline two prototypical applications that serve as demonstrators for further user tests and subsequent developments.

Keywords

Industrie 4.0; Workforce diversity; Human-machine interaction; Augmented reality

Introduction

The textile industry is the second largest consumer goods sector in Germany, with a focus on technical textiles. Industrial textile machines are used in the manufacture of various products e.g., clothing, lightweight construction, car interiors, or the field of medical technology. Germany’s textile industry - as a prominent example for western high-wage industries - is on the brink of change, due to both inherently social and technological effects. In this paper, we will firstly give an outlook on both these effects (cf. 2+3). Second, we will shortly describe the interdisciplinary build-up of our research group which influences the way how we address our research issues (cf. 4). Finally, we will outline two prototypical Augmented reality (AR)-based applications (apps) that serve as early demonstrators for further user tests and subsequent developments (cf. 5).

Materials and Methods

Concerning social reasons, a central aspect has to be seen in demographic changes: The current German workforce is increasingly aging, with a strong increase of employees aged 50 years and older. E.g., according to statistics of the German Federal Employment Agency from 2013, the number of employees older than 60 years increased from 2011 to 2012 by 12.5%. When compared to 2007, this share of personnel aged 60+ years even increased by 76.9% to a total of 1.654.831 people [1]. Overall, further increasement of this age group is prospected. Rather more, the currently high influx of migrants to Germany will soon lead to a more diverse workforce in terms of sociocultural and educational backgrounds. Hence, these demographic changes will have a massive impact in the German textile industry, too.

Technological Change: Human-Machine Interaction

At the same time, new production technologies based on Cyber- Physical Production Systems (CPPS) and the Internet of Things (IoT) are pushing their way onto the textile industry’s shopfloor [2-4], forming the basis for what has been labeled the Fourth Industrial Revolution ('Industry 4.0') by German government and enterprises alike [5]. Due to interaction with smart production machines together with progressive automation, overall industrial processes, work structures, and tasks of employees are changing on all organizational levels. Work tasks and job profiles are becoming more complex.

This holds true for the textile industry as well: Individual processes in the textile industry like weaving or finishing are highly automated-- especially in the field of technical textiles. Therefore, the handling of modern textile machines is more complex than before and requires increasing skills of the employees in operation and maintenance. For instance, the requirements of mechanics become more mechatronicsoriented and industrial electricians work more and more together with computer scientists.

As a consequence, more and entirely new skills will be needed for efficient and effective human-machine interaction in the near future ('HMI 4.0'). It can be assumed that classic technicians will primarily have to do creative ‘trouble shooting’ in the future and will therefore take on traits of knowledge workers [6,7].

The combination of both effects, i.e., increasing diversity of the workforce in the textile industry and increasing complexity of smart machines, creates the necessity of human-centered assistance systems that help the individual employee to improve his or her skills and to pass on knowledge to co-workers and colleagues.

SozioTex Research Group

Competence build-up in human-machine interaction for the textile industry

There has been very limited research on the combined social and technological effects on the workplace in the textile industry. Therefore, the interdisciplinary SozioTex team comprising engineers, sociologists, and educational scientists takes on the task of analyzing and evaluating the effects of increasing diversity as well as the increasing usage of highly complex Industrie 4.0-technology in the textile industry (Figure 1). Additionally, the SozioTex team designs, tests, and evaluates assistance systems that help cope with the aforementioned effects and minimize the discrepancies between young digital natives and older employees: The former adopt easily to new technologies but often lack professional experience, whereas the latter ones have more hands-on experience but have difficulties when facing working with new digital systems.

textile-science-engineering-adjustment

Figure 1: Vision of adjustment of social and technological change [8].

Prototypical Applications

Augmented reality-based human-machine interaction assistance

So far, the SozioTex team has designed two assistance systems [8,9]: The first one is based on the assumption that a suitable HMI 4.0 system forms a key element to integrate the flexibility of humans and their ability to handle complex tasks in a textile production unit. Therefore, an HMI 4.0 prototype is developed which serves to support human operators in a (momentarily lab-scale) production unit. The central component consists of smart glasses which serve as the user interface. This see-through wearable device augments the shopfloor reality with assistive information. Besides consuming information, shopfloor personnel is also enabled to give feedback to the production unit. Thus, a bidirectional communication channel between the human operator and the Smart Textile Factory is created [9-11].

The second assistance system is a mobile application for smartphones, tablets or smart glasses that makes use of augmented reality (AR) to assist the operator of a weaving machine. The AR application assists in the handling of weft yarn breakages by detecting where the breakage occurred and interactively showing how new yarn has to be inserted [9,11].

Furthermore, an important part of the SozioTex research draws on an algorithm that enables a method for multi-objective selfoptimization of the weaving process: This system is capable of calculating the optimal parameter settings with regard to user-defined preferences of objective functions. The self-optimization algorithm helps operators to set up a weaving machine with significantly reduced trial and error runs and changeover costs [12,13].

Conclusion and Outlook

To conclude, the adoption of such Industry 4.0 solutions in the textile industry and its effects on employees are assessed in cooperation with partners in industry and research and along with key user tests of demonstrator models. Furthermore, the compatibility of enterprises to processes is tested and recommended actions are deduced from best practice examples. Therefore, to sum up: the implementation of Industry 4.0-related technologies and systems will only prove successful if the employees are included in the process from the very beginning, as they have to be recognized as the ones who will integrate and use the systems.

Acknowledgment

We thank our colleagues for fruitful discussions and valuable feedback. Additionally, we would like to thank our student research assistants for their support, and especially our master`s students Bram Vanden Bergen and Gregory Longé for the first prototypical app implementations.

Moreover, we thank the German Federal Ministry for Education and Research for funding the SozioTex project within the programme ‘Interdisciplinary Competence Development with Research Focus on Human-Machine Interaction for the Demographic Change’.

References

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